It is well-known that the applicability of Linear Discriminant Analysis (LDA) to high-dimensional pattern classification tasks such as face recognition (FR) often suffers from the...
Juwei Lu, Konstantinos N. Plataniotis, Anastasios ...
A method is presented for modeling application performance on parallel computers in terms of the performance of microkernels from the HPC Challenge benchmarks. Specifically, the a...
Background: Principal component analysis (PCA) has gained popularity as a method for the analysis of highdimensional genomic data. However, it is often difficult to interpret the ...
Background: There is a vast need to find clinically applicable protein biomarkers as support in cancer diagnosis and tumour classification. In proteomics research, a number of met...
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...